Method and System for Representing Traffic Signals in a Road Network Database

ABSTRACT

A method and system for representing traffic control signals in a road network database is provided. The database may include lane-level modeling, intersection modeling, and traffic signal modeling of a road network. An individual traffic signal is represented in the database with data indicating the traffic signal&#39;s geographic location and other attributes of the traffic signal such as an arrangement of lenses in the signal, an indication as to whether the signal is vertically or horizontally oriented, a height of the traffic signal over the roadway, and others. The database can be used by a system in a vehicle that provides convenience features to the vehicle&#39;s driver. The system may attempt to warn or control a vehicle that is determined to be at imminent risk of violating a traffic signal.

REFERENCE TO RELATED APPLICATIONS

This present application is a continuation-in-part of U.S. patentapplication Ser. No. 10/620,732, entitled “METHOD OF REPRESENTING ROADLANES,” filed Jul. 16, 2003 which is a continuation-in-part of U.S.patent application Ser. No. 10/465,890, entitled “METHOD OF REPRESENTINGROAD INTERSECTIONS,” filed Jun. 19, 2003, the entire disclosures ofwhich are incorporated herein by reference.

FIELD OF INVENTION

The present invention relates to methods for representing roads as datain a database, and more particularly, to methods for representingtraffic control signals in a database used for vehicle driver assistancesystems.

BACKGROUND

Vehicle driver assistance systems, such as systems for obstacle warningand avoidance, lane departure warning, collision warning and avoidance,adaptive cruise control, adaptive transmission operation, automaticheadlight aiming, and so on, have been developed to improve theconvenience of vehicle operation. These systems include technologiesthat augment a driver's ability to operate a vehicle efficiently. Someof these systems include equipment that senses features around thevehicle. In addition, some of these systems use data that models a roadnetwork upon which the vehicle is traveling. Based on the sensedfeatures and the model of the road network, the driver assistancesystems may provide warnings or otherwise modify operation of thevehicle to improve convenience.

Data representations of the road network have also been used for variousother purposes. For example, data representations of the road networkare used in vehicle navigation systems to provide navigation-relatedfeatures, such as route calculation, route guidance, map display anddestination selection. In some databases used by navigation systems,each road segment is represented by one or more data records orentities. Associated with each data record or entity are attributes thatdescribe various features of the represented road segment. Some of thefeatures of a road segment that are represented by such data recordsinclude the location of the road segment, the locations of roadintersections, the name of the road segment, the speed limit (or speedcategory) along the road segment, the number of lanes along the roadsegment, any highway designations of the road segment, the type of roadsurface (e.g., paved, unpaved, gravel), the presence of any lanedividers, etc.

The ways that roads are represented in databases used in navigationsystems are useful. However, the ways that roads are represented indatabases used for navigation purposes may not be suitable for driverassistance systems. For example, for navigation purposes, it isimportant to have data that indicate the speed limits along roads, thenames of roads, the address ranges along road segments, and how muchtime it might take to cross a road intersection. For navigationpurposes, the exact path that a vehicle takes along a road segment isnot necessarily important unless the vehicle is approaching an upcomingmaneuver.

In addition, driver assistance systems may need or use other data incombination with sensors of the vehicle and the model of the roadnetwork to help the system provide instructions that would mimic adriver's response to a particular situation. For example, sensors ofdriver assistance systems may require data within the road databases toimprove object recognition based on a location or a type of the object.

Accordingly, it is an objective to provide a data model for additionalroad attributes, and in particular for traffic control devices, that canbe used by driver assistance systems.

It is another objective to provide a data model for traffic controldevices that is compatible with various uses of the data.

SUMMARY

To address these and other objectives, the exemplary embodiment includesa method and system for representing traffic signals as data. A databaseincludes traffic signal data entities that represent physical trafficsignals of an intersection in a road network. Each traffic signal dataentity may include data indicating a physical location of a representedtraffic signal, and data indicating at least one physical attributecorresponding to the represented traffic signal. The database mayadditionally or alternatively include a traffic signal cluster dataentity that includes data representing one or more traffic signalslocated at an intersection that, in parallel, control one or moreintersection maneuvers for traffic entering the intersection from aparticular road.

In another respect, the exemplary embodiment may take the form of amethod for representing traffic signals in a road database. The methodmay include storing in the road database traffic signal data entitiesthat represent physical traffic signals. The method may further includeassociating with each traffic signal data entity data indicating alocation of the represented traffic signal and data indicating at leastone physical attribute corresponding to the represented traffic signal.

In an alternative embodiment, the method may include identifying one ormore physical traffic signals located at an intersection that, inparallel, control one or more intersection maneuvers for trafficentering the intersection from a particular road. This alternativemethod may further include storing in the road database a traffic signalcluster data entity that includes data representations of the one ormore physical traffic signals.

The road database of the exemplary embodiment can be used by a driverassistance system in a vehicle to provide a convenience-related functionto a driver. The database may also be compatible with navigation-relatedapplications that use a different data model to providenavigation-related functions. These as well as other features,advantages and alternatives will become apparent to those of ordinaryskill in the art by reading the following detailed description, withappropriate reference to the accompanying drawings.

BRIEF DESCRIPTION OF FIGURES

FIG. 1 is an illustration of one example of an intersection.

FIG. 2 is a block diagram that shows one embodiment of components ofdriver assistance systems in the vehicle shown in FIG. 1.

FIG. 3 is a diagram that shows components of an embodiment of the roaddatabase of FIG. 2.

FIG. 4 is a diagram that shows components of one embodiment of one ofthe intersection objects shown in FIG. 3.

FIG. 5 is an exemplary illustration of a roundabout type ofintersection.

FIG. 6 is an exemplary illustration of a railroad crossing type ofintersection.

FIG. 7 shows the intersection depicted in FIG. 1 with exemplarytransversals of the intersection from some of the lanes illustrated.

FIG. 8 shows an exemplary intersection in which the transversals areinstantaneous.

FIG. 9 shows the intersection depicted in FIG. 1 with exemplary validvehicle paths for a transversal of the intersection from one lane toanother, illustrating that the transversal has a low confidence rating.

FIG. 10 is an illustration of an exemplary intersection located in ageographic area.

FIG. 11 is a block diagram that shows components of an embodiment of theroad database of FIG. 2.

FIGS. 12A and 12B are exemplary illustrations of overlapping lanes.

FIG. 13 is an exemplary illustration of a sublane and a datarepresentation thereof.

FIG. 14 is an exemplary illustration of an intersection with trafficsignals.

FIG. 15 illustrates an example traffic signal data entity.

FIG. 16 illustrates one example of a traffic signal cluster data entity.

FIG. 17 illustrates an exemplary data representation of the intersectionin FIG. 14.

FIG. 18 illustrates another example of an intersection.

FIG. 19 illustrates an exemplary data representation of the intersectionin FIG. 18.

FIG. 20 illustrates an exemplary data representation of anotherconfiguration of the intersection in FIG. 18.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

An exemplary embodiment relates to a method for representing trafficsignals for a road intersection in a database that contains data thatrepresent a road network in a geographic region. The database can beused by a system in a vehicle that provides convenience features to thevehicle driver. The database may include lane-level modeling,intersection modeling, and traffic signal modeling of a road network. Inthe exemplary embodiment, applications may use the database to attemptto warn or control a vehicle that is determined to be at imminent riskof violating a traffic signal. Thus, these applications may referencethe database to help determine the vehicle's position on the roadway (ata lane level), and a phase of any traffic signal(s) (e.g., green,yellow, red) that the vehicle is required to observe. These applicationsmay use sensors (e.g., cameras) to identify the phase of the trafficsignal, and may further benefit from (or even require) advance knowledgeof a traffic signal's placement and properties.

Providing knowledge of a traffic signal's placement and properties canfacilitate operation of a sensor, such as by guiding the sensor to viewdesired light sources from those within a camera image. For example, thesensor may have knowledge of where to look for traffic signals, and maythus use this knowledge to distinguish between other light sources inthat area, like vehicle headlights or taillights, street lights (forroad illumination), etc. In addition, providing knowledge of trafficsignal placement assists sensors to view a particular traffic signalcorresponding to a road lane in which a car is currently traveling.

In the exemplary embodiment, each individual traffic signal in ageographic region is represented in a database with data indicating thetraffic signal's geographic location and other attributes. Examples ofother attributes of a traffic signal can include: an arrangement of thelenses in the signal, an indication as to whether the signal isvertically or horizontally oriented, the height of the traffic signalover the roadway, and others.

In the exemplary embodiment, the database including representations oftraffic signals also includes representations of intersections and roadlanes, and an explanation of the intersection and road lane databaserepresentations will be given first. However, the database may beimplemented independently of the intersection and road lane datarepresentations so as to only include the traffic signalrepresentations.

I. Exemplary Intersection

FIG. 1 illustrates an exemplary intersection 10 located in a geographicregion. The intersection 10 is a location at which two roads meet at thesame level. A first road 14 is comprised of segments 18 and 22. A secondroad 26 is comprised of segments 30 and 34. These roads 14 and 26 eachhave two lanes in each direction. Each segment also has a left turn lane(e.g., 36). The left turn lanes do not extend along the lengths of thesegments. Instead, each left turn lane extends only part of the wayalong a segment. The intersection 10 and roads shown in FIG. 1 arerepresentative of many similar intersections and roads located in thegeographic region.

II. Driver Assistance System

A vehicle 40 travels on one of the roads. Although only one vehicle isshown in FIG. 1, the vehicle 40 is representative of many vehicles,which are similarly equipped, that travel on the roads in the geographicregion. Referring to FIG. 2, the vehicle 40 includes one or more driverassistance systems 44. The driver assistance systems 44 are systems thatmake operation of the vehicle more convenient. The driver assistancesystems 44 may include an obstacle warning system, a lane departuresystem, an adaptive cruise control system, and/or a collision avoidancesystem. The driver assistance systems 44 may include other systems inaddition to, or instead of, any of these systems.

It should be understood that this and other arrangements describedherein are set forth for purposes of example only, and otherarrangements and elements can be used instead and some elements may beomitted altogether. Further, many of the elements described herein arefunctional entities that may be implemented as hardware, firmware orsoftware, and as discrete components or in conjunction with othercomponents, in any suitable combination and location. Still further, anyof these or other entities that are described herein as carrying out aparticular function could include a processor and data storage holdingan appropriate set of program instructions (e.g., machine languageinstructions) executable by the processor to carry out that function.

The driver assistance systems 44 are combinations of hardware andsoftware components. The driver assistance systems 44 use sensors 48.Various different types of sensors may be used. In general, the sensors48 measure (or are responsive to) some property, parameter, attribute,or characteristic of the vehicle or the environment around the vehicle.For example, the sensors 48 may include a radar system 48(1), a camerasystem 48(2), or other sensors.

The vehicle 40 includes a positioning system 50. In the embodiment shownin FIG. 2, the positioning system 50 is part of the driver assistancesystems 44. Alternatively, the positioning system 50 may be part ofanother system in the vehicle 40, such as a navigation system 51.According to another embodiment, the positioning system 50 may be astandalone system in the vehicle. The positioning system 50 is acombination of hardware and software components. For example, thepositioning system 50 may include a Global Positioning System (GPS) or aDifferential Global Positioning System (DGPS) unit 50(1), one or moreinertial sensors 50(2), such as a gyroscope or accelerometer,differential wheel sensors, or other types of equipment.

In a present embodiment, the driver assistance systems 44 include or usea road database 60. The road database 60 may be stored on any type ofcomputer-readable medium. The road database 60 includes a datarepresentation of the road network in the geographic region in which thevehicle 40 is traveling. In a present embodiment, the road database 60includes data that indicate the positions of the roads, theintersections of roads, the locations of lanes, the locations andattributes of traffic signals, as well as other information.

The road database 60 is used by an application 50(3) in the positioningsystem 50 to determine the position of the vehicle 40 relative to theroad network. More specifically, the positioning application 50(3) usesthe data in the road database 60 and outputs from other positioningsystem components, such as the GPS unit 50(1) and inertial sensors50(2), to determine the position of the vehicle along a road segmentrepresented by data in the road database 60, the position of the vehiclerelative to the lanes of the represented road segment, the directionand/or bearing of the vehicle along the represented road segment, andpossibly other parameters.

The driver assistance systems 44 also include driver assistanceapplications 52, which are programs that implement the functions of thedriver assistance systems 44. The driver assistance applications 52receive outputs from the sensors 48. The driver assistance applications52 also use data from the road database 60. The driver assistanceapplications 52 may also receive other information. Based on the datareceived from the sensors 48, the data obtained from the road database60, and possibly other information, the driver assistance applications52 evaluate whether a warning or other action should be provided. Thedriver assistance systems 44 provide the convenience features via a userinterface 62 of the vehicle or by controlling a vehicle mechanicalsystem 64. For example, a curve warning application may provide anaudible alarm via speakers (i.e., part of the user interface 62 in thevehicle) or an obstacle avoidance application may engage the vehicle'sbrakes (i.e., one of the mechanical systems 64 in the vehicle).

III. Road Database

FIG. 3 shows components of the road database 60. In the embodiment shownin FIG. 3, roads are represented in different ways. These different waysrelate to how the road data are used. The different ways that the roaddata are being used affect which aspects of a road are represented. Forexample, in FIG. 3, the road database 60 includes navigation data 80 andphysical configuration data 82. (In addition to navigation data 80 andphysical configuration data 82, the road database 60 may include othercollections of data that represent the roads in other ways.) In FIG. 3,the navigation data 80 and the physical configuration data 82 areindicated as being separate collections that are related to each other.However, in alternative embodiments, these different ways ofrepresenting roads may be included in a single collection of data.

The navigation data 80 are used by navigation-related applications, suchas route calculation, route guidance, destination selection, and mapdisplay. The navigation data 80 represent the aspects of roads that areimportant for these functions, such as which roads connect to eachother, road names, speed limits along roads, address ranges along roads,and so on.

In the embodiment of FIG. 3, the navigation data 80 include data thatrepresent road segments 84 and data that represent nodes 86. Eachdiscrete segment of each road is represented by a separate road segmentdata record. A road segment is a portion of a road between adjacentintersections or between a dead end and an adjacent intersection. A roadsegment may also be defined that ends at a point along a road betweenadjacent intersections. The navigation data 80 in the road database 60may also include data records that represent aggregations of individualroad segments.

A node refers to an endpoint of a road segment. For example, each roadsegment has two endpoints. Each endpoint of a road segment isrepresented with a node data record in the road database 60.

IV. Representation of Intersections

As mentioned above, the road network database 60 also includes physicalconfiguration data 82. The physical configuration data 82 are used bythe driver assistance systems (44 in FIG. 2) for convenient features,such as obstacle warning, curve warning, and so on.

The physical configuration data 82 provides a representation of the roadnetwork that is different from the representation provided by thenavigation data 80. For example, the physical configuration data 82represent detailed aspects of the road lanes (including laneconfiguration), detailed aspects of the intersections, traffic signals(and placement thereof), shoulder locations, and other detailed physicalfeatures relating to roads. Where roads intersect, the physicalconfiguration data 82 models the relationships between the lanes thatbring traffic into the intersection and the lanes that take traffic out.Modeling these relationships involves several considerations. Forexample, simply extending road lanes into an intersection area wouldlead to many lane-to-lane crossings that would imply connectivitybetween crossing lanes that may not be present in reality. In addition,if connectivity between lanes does exist, a simple extension of thelanes into the intersection area might indicate the point of theconnectivity in the wrong place. For these reasons, as well as for otherreasons, the physical configuration data 82 in the road database 60includes a road lane data model that has road lanes that lead up to, butnot through, intersections.

The following considerations are addressed by an intersection model usedin the physical configuration data 82 in the road database 60:

(1) The road-to-road maneuvers that take place at an intersection,between specific lanes on the incoming and outgoing lanes, aredescribed. In particular, a driver assistance application, in a vehicleheading into and through an intersection, is provided with theinformation needed to predict a likely vehicle location at some time ordistance offset from the current vehicle position.

(2) The fact that some maneuvers through an intersection havepredictable vehicle paths, whereas other maneuvers through theintersection do not have a predictable path, is accommodated.

(3) The interaction between traffic signals and traffic at theintersection is modeled. This modeling accounts for the case in whichsome traffic lanes or maneuvers are controlled by different aspects ofthe traffic signals (e.g., a left-turn signal). This modeling alsoaccounts for the case in which some maneuvers at an intersections aregoverned by traffic signals and other maneuvers at the same intersectionare not (e.g., a “Yield” on a right turn).

(4) Normal intersections are distinguished from special types ofintersections such as roundabouts and railroad crossings that posespecial considerations for driver assistance systems.

To support compatibility with navigation-related applications, therepresentations of intersections in the physical configuration data 82are associated with the node data that represent the same correspondingactual physical intersections in the navigation data 80. Some actualphysical intersections are represented by more than one node data recordin the navigation data 80. For example, an intersection between amultiple-digitized road and a single digitized road may be representedby two or more node records in the navigation data 80. In such cases,the representation of an intersection in the physical configuration data82 is associated with all the node records in the navigation data 80that represent the same intersection.

Another consideration associated with the representation of anintersection in the physical configuration data 82 is that therepresentation should be reliably derivable from practical sourcematerials. For example, the representation of an intersection in thephysical configuration data 82 should be derivable from vehicle pathdata obtained from driving, overhead aerial imagery, or probe vehicle(“floating car”) data.

The above considerations are addressed in an embodiment of the physicalconfiguration data 82 disclosed herein. Referring again to FIG. 3, thephysical configuration data 82 of the road database 60 includesintersection objects 90, lane data entities (or records) 100, andtraffic signal data entities 106, as well as other data entities.

An intersection object 90 is a data entity in the road database 60. In apresent embodiment, the intersection object 90 does not define shape ordetermine a position. Instead, the intersection object 90 defines thelogical associations between the other data entities that represent thevarious physical components of the actual intersection. An intersectionobject 90 is defined for each road-to-road intersection represented inthe road database 60.

Referring to FIG. 4, each intersection object 90 is identified by aunique ID, (e.g., an intersection object ID 90(1)).

Each intersection object 90 is logically associated with (i.e.,references) one or more of the nodes (by node ID) that represent theintersection in the navigation data 80. Accordingly, each intersectionobject 90 includes a reference 90(2) to one or more node IDs. Byreferencing the node IDs that represent the intersection in thenavigation data 80, the intersection object 90 associates therepresentation of the physical configuration of the road with thenavigation representation of the road network.

Each intersection object 90 includes an attribute 90(3) that identifiesthe intersection type. The intersection type attribute 90(3) identifiesthe represented intersection as “standard,” “roundabout,” or “railroadcrossing.” Most represented intersections are “standard.” Anintersection like the one in FIG. 1 (i.e., intersection 10) would berepresented as a “standard” intersection.

As another example, an intersection like the one in FIG. 5 (i.e.,intersection 102) would be represented as a “roundabout” intersection.Having information that indicates that an intersection is a roundabout(also sometimes referred to as a traffic circle) is useful for driverassistance applications that involve sensing the path ahead of avehicle. When a vehicle enters a roundabout intersection, it follows acircular path in a single rotational direction around a center island ofthe roundabout. Thus, the vehicle entering a roundabout from an entrylane may actually travel in a direction away from the exit lane as ittravels around the roundabout. A driver assistance application thatsenses the path ahead of the vehicle uses the information that anintersection is a roundabout to account for the vehicle path travelingaround the roundabout.

As still another example, an intersection like the one in FIG. 6 (i.e.,intersection 104) would be represented as a “railroad crossing”intersection. Note that an intersection indicated to be a “railroadcrossing” is not necessarily an intersection of actual roads. However,in a present embodiment, railroad crossings are represented byintersection objects, in part because of the presence of metal railsthat may be detected by in-vehicle sensors. A railroad crossing issimilar to a road crossing, in that the lanes may not be well definedthrough the crossing. A railroad crossing may present radar targets (notonly trains but also metal rails), and may have marked stoppingpositions.

Referring to FIG. 4, the intersection object 90 includes a maneuver list90(4). The maneuver list 90(4) includes entries for all the reasonable,legal transversals from a lane entering the represented intersection toa lane leaving the represented intersection. For example, referring toFIG. 7, the maneuvers from three of the lanes 110, 112 and 114 enteringthe intersection 10 are shown. The lane 110 that enters the intersection10 has one maneuver 120 onto the lane 122 and another maneuver 124 ontothe lane 126. The lane 112 that enters the intersection 10 has only onemaneuver 128, i.e., onto the lane 130. Likewise, the lane 114 thatenters the intersection 10 has one maneuver 132 onto the lane 134. (Forthe sake of clarity, FIG. 7 illustrates the maneuvers from only thethree lanes 110, 112, and 114 that enter the intersection 10 from theroad segment 22. It is understood that the intersection object thatrepresents the intersection 10 would include all the maneuvers from allthe lanes from all the rest of the road segments that enter theintersection.)

Each entry in the maneuver list 90(4) includes several kinds of dataabout the represented transversal. Referring again to FIG. 4, an entryin the maneuver list 90(4) identifies the entry lane 90(4)(1) and theexit lane 90(4)(3) for the maneuver. The entry lane and the exit laneare identified by lane data entity IDs. In the embodiment of FIG. 4, theentry in the maneuver list 90(4) also indicates the segment of which theentry lane is a part 90(4)(2) and the segment of which the exit lane isa part 90(4)(4). In this embodiment, these segments are identified byroad segment IDs (i.e., references to the road segment records in thenavigation data 80).

An entry in the maneuver list 90(4) also identifies a geometry 90(4)(5)of the maneuver. At a minimum, the geometry 90(4)(5) is identified as astraight line between the end of the incoming lane 90(4)(1) and thestart of the outgoing lane 90(4)(3). If the entry and exit lanesphysically meet (such as in the intersection 136 illustrated in FIG. 8),the geometry 90(4)(5) indicates the single point where the entry andexit lanes physically meet. If the travel path of a vehicle between theentry lane and the exit lane is curved, this geometry 90(4)(5) mayindicate this path by defining a parametric curve.

An entry in the maneuver list 90(4) also includes a confidenceindication 90(4)(6). The confidence indication 90(4)(6) relates to themaneuver's geometry 90(4)(5). The confidence indication 90(4)(6)indicates a likelihood that the geometry of the maneuver accuratelypredicts or represents a vehicle path. For example, it is possible thata basic straight-line connection between an entry lane and an exit laneis highly indicative of actual vehicle paths, such as when goingstraight through an intersection. It is also possible that even for aturning maneuver, the vehicle path is highly predictable and well known.However, it is also possible that the vehicle path geometry through amaneuver is variable or even unknown.

FIG. 9 shows several possible paths of the intersection 10, labeled 140,142 and 144, that a vehicle could legally take when traveling from theleft turn lane 114 on the road segment 22 onto the lane 134 on the roadsegment 34. Each of these several possible paths is a legal path. Theentry for this transversal in the maneuver list 90(4) in theintersection object 90 that represents this intersection would includethe geometry for only one of these paths. In addition, the maneuverentry for this transversal would have a low confidence indication90(4)(6), i.e., meaning that the probability of the vehicle actuallybeing on the path indicated by the geometry 90(4)(5) is relatively low.This confidence indication 90(4)(6) is used by driver assistanceapplications (e.g., 52 in FIG. 2) to determine if a vehicle's deviationfrom the maneuver geometry is of concern.

In a present embodiment, the confidence indication 90(4)(6) is set toone of several values. These values include the following (however othervalues are possible as well):

(1) None—When the confidence indication 90(4)(6) is set to “None”, thegeometry 90(4)(5) is set to indicate a straight-line connection.However, this straight line geometry is not intended to represent anactual vehicle path.

(2) Instantaneous—When the confidence indication 90(4)(6) is set to“instantaneous”, the incoming and outgoing lanes meet with no gap orcross-traffic. An example of an intersection with no gap between theincoming and outgoing lanes and therefore an instantaneous confidenceindication, is shown in FIG. 8.

(3) Actual, high confidence—The confidence indication 90(4)(6) is set to“Actual, high confidence” when the geometry is based on accurate sourcessuch as probe vehicle data with small statistical variance.

(4) Actual, variable—The confidence indication 90(4)(6) is set to“Actual, variable” when the geometry is based on sources that indicate ahigher statistical variance.

(5) Cartooned, high confidence—The confidence indication 90(4)(6) is setto “Cartooned, high confidence” when the geometry is typically, astraight-line connection for a straight-through maneuver between lanesthat line up well.

(6) Cartooned, medium confidence—The confidence indication 90(4)(6) isset to “Cartooned, medium confidence” when the geometry is digitizedfrom tire artifacts or other evidence that does not provide astatistical variance.

(7) Cartooned, low confidence—The confidence indication 90(4)(6) is setto “Cartooned, low confidence” when the geometry is digitized logicallybut without supporting evidence.

An entry in the maneuver list 90(4) also includes an indication 90(4)(7)as to whether the maneuver is the “most likely path” for traffic comingfrom the associated incoming lane. This indication may be meaningfulwhen two or more maneuvers are possible from the same lane. This willhelp a driver assistance application (e.g., 52 in FIG. 2) determine alikely lane-level position.

An entry in the maneuver list 90(4) also includes an indication 90(4)(8)as to whether traffic signals are present at the intersection and anindication as to which particular signal(s) govern traffic for thismaneuver (described in more detail below). It is possible that allmaneuvers for a particular incoming lane will share the same signals,but it is also possible that maneuvers for different incoming lanes willbe governed by different traffic signals.

In addition to the information indicated above, the intersection object90 may include additional data.

V. Representation of Road Lanes

Referring back to FIG. 3, the physical configuration data 82 alsoincludes lane data entities 100. The lane data entities 100 identifyeach lane of each road in the geographic region. The lane data entity100 includes a data entity ID that uniquely identifies the lane datarecord in the road database 60. Each lane data entity 100 identifieswhich road the lane is part of (e.g., by reference to a road segment IDin the navigation data 80), the location of the lane (e.g., the startinglocation, the ending location, and the shape of the lane between thestarting location and the ending location), and what is adjacent to thelane. The lane data entity may include other information as well.

FIG. 10 illustrates an exemplary road segment 150, which is part of aroad network located in a geographic region, represented by a lane dataentity. The road segment 150 comprises a portion of a road between twoadjacent intersections 152 and 154. Other road segments (not shown)connect to the intersections 152 and 154. The road segment 150 can beaccessed by a vehicle from the other road segments via intersections 152and 154.

The road segment 150 has several lanes in each direction. For example,the road segment 150 includes lanes 158, 160, 162, and 164 extendingbetween the intersections 152 and 154. The lanes 158 and 160 aredesigned to carry vehicle traffic only in the direction from theintersection 152 to the intersection 154 and the lanes 162 and 164 aredesigned to carry vehicle traffic only in the direction from theintersection 154 to the intersection 152.

In addition, the road segment 150 includes some lanes that do not extendthe entire length between the intersections 152 and 154. For example,the road segment 150 includes a left turn lane 166 leading into theintersection 154 and another left turn lane 168 leading into theintersection 152. These left turn lanes 166 and 168 extend only part ofthe way along the road segment 150. In addition, the road segment 150includes a right turn lane 170 leading into the intersection 154. Theright turn lane 170 extends only part of the way along the road segment150. Further, the road segment 150 includes some lanes that form or endgradually over a longitudinal distance. Examples of gradually forminglanes are shown at 172 and 174.

The road segment 150 is one of many road segments that form the roadnetwork in the geographic region. The other roads segments may havedifferent shapes and may have more lanes or fewer lanes.

Referring to FIG. 11 a more detailed illustration of the road database60 is presented. In the present embodiment, the road database 60 takesinto account that on the actual road network, some lanes form or endgradually over a longitudinal distance, such as lanes 172 and 174 inFIG. 10. In the physical configuration data 82, lane data entities 100are used in the road database 60 to represent whole portions of roadlanes. A whole portion of a road lane includes that part where bothedges of the lane are discernable and the lane is at full width. In thephysical configuration data 82, a portion of a lane where the lane is atless than full width is not modeled as a lane, i.e., with a lane datarecord. Instead, a portion of a lane where the lane is at less than fullwidth is modeled relative to the adjacent lane from which the partiallane is gradually forming (or merging into). A data attribute of theadjacent lane (or lanes) is used to indicate that a lane is starting orending adjacent thereto. This way of modeling gradually forming ormerging lanes is compatible with the relative uncertainty associatedwith the paths for cars entering or leaving a lane that is forming orending. A lane centerline is not provided for a partial width lane(i.e., where a lane is starting or ending gradually over a longitudinaldistance). The data representation of gradually forming (or merging)lanes is described in more detail below in connection with the adjacencyattributes.

The following considerations relate to the way lanes are represented inthe physical configuration data 82.

(1) Lanes are represented so that they do not cross one another.

(2) A lane is represented so that it goes up to, but not through, theintersection at the end of the road segment of which it is a part. (Thismay prevent any implied connectivity between lanes that is notconsistent with reality.)

(3) An actual road lane may continue unbroken across multiple roadsegments, such as when a ramp splits off from (one lane of) the road.However, when a lane is represented in the physical configuration data82, the lanes of each road segment are modeled separately. In otherwords, a lane, as represented in the physical configuration data 82,does not extend beyond the end of the road segment of which it is apart.

In the embodiment of FIG. 11, the physical configuration data 82 iscompatible with the navigation data 80. This allows navigation-relatedapplications (in the navigation system 51 in FIG. 2) to be compatiblewith driver assistance applications (52 in FIG. 2). This compatibilityis supported in the road database 60 by including references between thenavigation data 80 and the physical configuration data 82. For example,a representation of a lane in the physical configuration data 82 mayrefer to (e.g., by data record ID) the data record in the navigationdata 80 that represents the road segment of which the lane is a part.

In the physical configuration data 82, the lane data record 100 includesvarious attributes that describe features and/or aspects of therepresented lane. Some of the attributes of a lane include a “directionof travel”, the “type of lane”, a “validity period” and “accesscharacteristics,” for example.

Some of the different types of lanes include a “through lane”, a “leftturn lane”, a “right turn lane”, a “center turn lane”, a “leftshoulder”, a “right shoulder”, a “merge”, and a “ramp,” for example. Thelane type “left shoulder” or “right shoulder” are used with a “validityperiod,” as explained below. Full-time shoulders are not coded as lanes.“Left shoulder” and “right shoulder” are defined with respect to thedriver's orientation. In a present embodiment, some combinations areallowed (e.g., through, left turn, and/or right turn can all be appliedto the same lane at the same time).

The lane attribute “validity period” is used when a lane has differentuses at different times (e.g., a shoulder that is used for throughtraffic at certain hours).

The lane attribute “access characteristics” includes a “yes/no”indicator for different vehicle types, such as automobiles, buses,taxis, trucks, bicycles, pedestrians, emergency vehicles, carpools,deliveries, through-traffic, and so on.

Additional lane attributes may include road condition, roadside barrier,toll booth, lane marker type, road surface type, lane width, speed, andadjacency. (The adjacency attribute is described in more detail below.)If two lanes split, an attribute may be included that indicates thatthese lanes overlap. In the case of a true lane split, two lanes aremodeled such that their centerlines start at the same point. These areattributed as “overlapping” to indicate that two lane surfaces sharesome of the same pavement. One example of overlapping lanes is shown inis FIG. 12A. FIG. 12A shows three lanes on three different roadsegments. The road segments (and lanes) in FIG. 12A connect in aY-shaped configuration. Overlapping lanes can also occur on a singleroad segment. An example is shown in FIG. 12B.

In the physical configuration data 82, each data lane data entity 100 isassociated with data 180 that defines the geometry of the lane. Thegeometry of a lane includes the longitudinal shape of the lane. Forpurposes of defining the longitudinal shape of a lane, a centerline ofthe lane is determined and used to represent the longitudinal shape. Adata representation of a lane 100 includes data that defines the lanecenterline for every whole portion of a road lane. The centerline isdefined as the line midway between the lane edges. Lane edges can belane markings (such as paint) and/or physical edges (such as a curb,median or edge of pavement). Defining lanes in this manner facilitatesrepresentation of lanes by making the data creation process reliable andreproducible.

The shape of the lane centerline can be expressed in various ways. Someof these ways include parametric curvatures or sets of shape pointsinterpolated by straight line segments (e.g., a “polyline”). Examples ofparametric curvatures include, but are not limited to, uniformB-splines, non-uniform B-splines, and clothoids.

The physical configuration data 82 includes data 182 that provides fordefining attributes that apply to only a longitudinal subset of a lane.A longitudinal subset of a lane is referred to as a “sublane.” In thephysical configuration data 82, a sublane is defined by a pair of pointsalong the lane, expressed as distances along the lane centerline fromone end (e.g., a designated end) of the lane. In the embodiment of FIG.11, a sublane is not defined to have geometry of its own. Instead, thegeometry of the lane (of which the sublane is a part) is applied to thesublane. Defining sublanes in this manner allows attributes to begin andend as necessary along a lane without complicating the underlying lanegeometry.

When a sublane is defined, the attributes associated with the sublanesupersede those same attributes of the associated lane. For example,FIG. 13 shows a physical lane 200 that has left and right shoulders 202and 204 except for a portion 206. The portion 206 has a right shoulder,but on the left side has a barrier. In the physical configuration data82, this lane would be represented by a lane data entity 208 thatincludes adjacency attributes that indicate that the lane 200 hasshoulders on both sides. The lane data entity 208 would include roadsidebarrier attributes that indicate that the lane has no barriers on eitherside. In addition, a sublane data entity 210 would be defined for thelane 200. The sublane data entity would indicate a starting point and anending point along the lane. The sublane data entity 210 would includeadjacency attributes that indicate that the lane has no drivable surfaceon the left side. In addition, the sublane data entity 210 would includeroadside barrier attributes that indicate that the lane has a roadsidebarrier on the left side. Thus, for that portion of the lane 200 thatcorresponds to the sublane 206, the attributes of the sublane dataentity 210 would apply instead of the attributes of the lane data entity208.

In a present embodiment, only those fields of a sublane data entity arepopulated that are different from the corresponding fields in the lanedata entity that represents the lane of which the sublane is a part.Accordingly, in FIG. 13, the sublane data entity does not contain anyinformation regarding the adjacency or barrier on the right side becausethe right-side adjacency and barrier situation of the sublane is notdifferent than on the rest of the lane.

Several considerations apply to sublanes. A sublane does not extend pastthe end of the lane of which it is a part. Multiple sublanes may bedefined for each lane. Sublanes may overlap each other, except thatsublanes that overlap cannot change the same lane attributes. Sublanesthat do not overlap may change the same lane attributes.

Another of the attributes associated with the data representation oflanes 100 is data that indicates what is next to the represented lane oneach side thereof. In one embodiment, each lane data entity 100 includesadjacency attributes 184. The adjacency attributes 184 indicate whatlies to the left and right of a represented lane beyond the laneboundary. This attribute can be applied to the whole lane and also to alongitudinal subset of the lane (a “sublane”).

The adjacency attribute may include data that indicate any of thefollowing conditions:

(1) another lane, which can be entered by a lane change,

(2) another lane but which cannot be entered,

(3) a lane that is in the process of forming,

(4) a lane that is in the process of ending,

(5) a shoulder,

(6) another “drivable surface”, e.g., not a lane or shoulder, but asurface that might have a vehicle on it, such as a parking lane or lowmedian, or

(7) no drivable surface, e.g., a drop-off, a barrier, etc.

This adjacency attribute 184 provides information that enables a driverassistance system (e.g., element 44 in FIG. 2) to determine anappropriate warning or operation relating to a lateral lane change. Forexample, the information provided by the adjacency attribute can be usedto define where a lane change can legally occur. The informationprovided by the adjacency attribute can also be used to determine whereother vehicles are likely to be present.

There are several additional considerations relating to the way that thephysical configuration data represents lanes.

There is often (but not always) lateral connectivity between parallellanes of a road that carry traffic in the same direction. For manyroads, a vehicle traveling in one lane may change lanes at any point.This lateral connectivity is modeled with the embodiment disclosedherein. According to this embodiment, there may not be any particularpoints at which traffic can change from one lane to another, and thepaths taken by vehicles to effect lane changes may vary, depending ondriver preference and influenced by speed and traffic conditions.

Lanes can begin or end in the middle of a roadway, causing vehicle pathsto move into or out of lanes. In the transitional areas where lanesbegin or end, the physical centerline of the narrowing/widening lane maynot correspond to a likely vehicle path. Moreover, the vehicle paths ofcars entering or leaving forming or merging lanes are not necessarilypredictable in many cases.

Lane-specific attributes may change at any longitudinal point along alane. Different lanes along a road may have attribute changes atdifferent longitudinal points. The embodiment disclosed herein providesfor these changes by defining sublanes that have attributes thatsupersede those of their associated lanes.

In one embodiment disclosed herein, support is provided for representingthe geometry of a lane more accurately than in conventional roaddatabases. This higher level of accuracy may be required by some driverassistance applications.

Another consideration associated with the representation of lanes in thephysical configuration data 82 is that the representation should bereliably derivable from practical source materials. For example, therepresentation of lanes in the physical configuration data 82 should bederivable from vehicle path data obtained from driving, overhead aerialimagery, or probe vehicle (“floating car”) data.

As mentioned above, according to some embodiments, a lane that is lessthan full width is not modeled as a lane (i.e., with a data record), butinstead is modeled as an attribute of an adjacent lane (or a sublane ofan adjacent lane). In one alternative embodiment, lanes that are lessthan full width can be modeled as lanes. According to this alternative,lanes that are less than full width are represented using lane dataentities. In this alternative, data entities that represent these typesof lanes include an attribute that indicates that the represented laneis less than full width (e.g., a “transitioning lane”). A data entitythat represents a transitioning lane may include some or all theattributes of a full lane. For example, a data entity that represents atransitioning lane may indicate start and end points. A data entity thatrepresents a transitioning lane may also include adjacency attributes.The adjacency attributes of a transitioning lane would indicate whatfeatures are located next to the transitioning lane. A data entity thatrepresents a transitioning lane may also include a centerline. Thecenterline of a transitioning lane may be determined from the actualphysical dimensions of the transitioning lane or alternatively thecenterline may be estimated from the start and end points of thetransitioning lane.

VI. Representation of Traffic Signals

Referring again to FIGS. 3 and 11, the physical configuration data 82 ofthe road database 60 further includes traffic signal data entities 106.A traffic signal data entity 106 may correspond to a specificintersection object 90, since a physical traffic signal represented bythe traffic signal data entity 106 is located at an intersection. Thetraffic signal data entity 106 includes data representing informationabout a location and other attributes of a physical traffic signal.Although the term traffic signal is used, this term encompasses any typeof traffic light, or traffic control signal (which may be referred to asroadside indicators), and other signals that are used to controltraffic.

FIG. 14 illustrates an exemplary intersection 250 with traffic signals.There are five different traffic signal faces controlling the roadheading up from the bottom of the picture: a “left turn only” signal 252at the far left, and three signals on structures just beyond theintersection; one left turn only signal 254, and two signals 256 and 258for straight and right-turn traffic. A signal 260 for straight andright-turn traffic is on the right side just before the intersection.

As illustrated in FIG. 14, the intersection has multiple trafficsignals, and some of the signals apply to a vehicle based on itsposition, e.g., a left-turn signal will not apply to a vehicle in astraight-thru-only lane. Thus, there can be a “many to many”relationship between traffic signals, map elements and possibleintersection maneuvers. These considerations are addressed by thepresent embodiment. Some driver assistance applications, such asintersection warning applications, require detection of appropriatetraffic signal operations. Information about the location and operationof traffic signals in the database helps to achieve this goal.

FIG. 15 illustrates an example of a traffic signal data entity 106,which is a data structure within the road database 60 (illustrated inFIG. 3). The traffic signal data entity 106 includes a traffic signalidentifier (ID) 106(1), location data 106(2), and attribute data 106(3).The traffic signal data entity 106 may include other data as well. Asingle intersection may have multiple traffic signal locations, each ofwhich applies to some or all of the lanes on the road that the trafficsignal controls. Thus, each “signal face” is maintained as a trafficsignal data entity. In a present embodiment, only traffic signals thatare capable of multiple phases (stop, go, etc.) are represented by atraffic signal data entity 106. Fixtures with one lens, such as“blinking red” (stop) or “blinking yellow” (caution) are excluded, asare railroad crossing signals. “Blinking red” single-phase signals maybe included in the road database 60 as stop signs. However,multiple-phase signals can be included and represented as traffic signaldata entity, even if they serve at some times as single-phase signals(e.g., “blinking yellow” in off-peak hours).

The location data 106(2) in a traffic signal data entity 106 defines amap position (e.g., latitude and longitude coordinates) of the locationof the physical traffic signal that the data entity represents. Thelocation may be indicated at a 0.5 m or finer precision with an accuracyrequirement at 2 m lateral and 3 m longitudinal, for example. This willenable an application to limit its object recognition techniques torelevant positions. If a traffic signal fixture has multiple faces, eachcontrolling different roads, each face is considered a separate trafficsignal and accordingly each face is represented by a separate trafficsignal data entity. Thus, it is possible for multiple traffic signaldata entities to have the same geographic coordinate location.

The attribute data 106(3) of a traffic signal data entity includes datathat describe other aspects of the represented traffic signal. Forexample, the attribute data 106(3) can include an indication as to anarrangement 106(3)(1) of the lenses in the traffic signal. In a presentembodiment, the arrangement data 106(3)(1) indicates whether therepresented traffic signal has “3 lenses” (i.e., red/yellow/green) or“other.” A represented traffic signal is indicated as being a three-lenssignal if the signal consists of exactly 3 lenses, which can be round,arrow, or combination. Some turn signals have additional lenses (e.g., 3round signals plus turning arrows), and these types of signals are codedas “other”, i.e., non-three-lens signals. This information assists inobject recognition. In an alternative embodiment, the attribute data106(3) can provide a more detailed description of the lens arrangementin the traffic signal face, such as exactly how many lenses are present,what colors are located in which positions, circles versus arrows.

The attribute data 106(3) also may include an indication of theorientation 106(3)(2) of the traffic signal, such as whether the signalis vertically or horizontally oriented. This will also assist ineffective object recognition.

The attribute data 106(3) may also include data indicating a height106(3)(3) of the traffic signal over the roadway. The height couldalternatively (or additionally) be included as data within the location106(2) of the traffic signal, if for example, the location is given aslatitude, longitude, and altitude coordinates.

Further, the attribute data 106(3) may include an indication as to atype of the signal 106(3)(4), such as whether the signal is a “left turnsignal,” i.e., affords protected left turns during a phase whenthru-traffic is stopped. This may be a signal with arrow lenses, orround lenses with a sign indicating that it is a left turn signal. Thismay facilitate an application interpreting a signal's green (or red)phases when applied to thru-traffic. Other types of traffic signalsexist as well, and are well-known.

Referring again to FIG. 3, the physical configuration data 82 of theroad database 60 further includes traffic signal cluster data entities(illustrated as ‘other’ in FIG. 3). It is common for a particulartraffic signal to control more than one lane or maneuver in anintersection. It is also common for an intersection to have redundanttraffic signals, i.e., multiple traffic signal heads that convey thesame information. To simplify the relationships between traffic signalsand maneuvers, and to avoid a many-to-many relationship, “traffic signalclusters” can be used.

FIG. 16 illustrates one example of a traffic signal cluster data entity280. Sets of one or more traffic signals at an intersection that operatein tandem (identical phases) are logically grouped into a “trafficsignal cluster.” Thus, the traffic signal cluster is defined as aspecific set of one or more traffic signal data entities that, inparallel, control one or more intersection maneuvers for trafficentering an intersection on a particular road. Each physical trafficsignal in the set of traffic signals in a traffic signal cluster will bephysically located at the same intersection, but will have differentgeographic coordinate locations (since the traffic signals are notpositioned on top of one another). Since there are commonly multipletraffic signals at an intersection, using traffic signal clustersaddresses “many-to-many” database relationships, and enables anintersection maneuver to be assigned a unique traffic signal dataentity. The traffic signal cluster 280 may include a traffic signalcluster identifier (unique ID) 282 and a traffic signal location ID 284,which identifies the traffic signal data entity that represents thephysical traffic signal.

The traffic signal cluster 280 is also associated with one or moreintersection maneuvers corresponding to the traversals which aregoverned by these traffic signals, and thus is associated with anintersection maneuver ID 286 that corresponds to an intersection object90. For example, the intersection maneuver ID 286 may correspond to anentry in the maneuver list 90(4) (e.g., entry 90(4)(8)) as shown in FIG.4, that indicates which particular signal(s) govern traffic for thismaneuver). A particular intersection maneuver will be associated with atmost one traffic signal cluster. This may enable proper representationof the relationship between traffic signals and actual traffic, even forlanes where traffic signals govern traffic differently even for vehiclesin the same lane, depending on the intended maneuver (e.g., a “left turnon arrow only” signal for a lane that allows both left-turn andstraight-thru traffic).

A. First Exemplary Traffic Signal Representation

FIG. 17 illustrates a data representation of the intersection 250 inFIG. 14. Traffic signal 252 is represented by traffic signal ID 2064,traffic signal 254 is represented by traffic signal ID 2065, trafficsignal 256 is represented by traffic signal ID 2066, traffic signal 258is represented by traffic signal ID 2067, and traffic signal 260 isrepresented by traffic signal ID 2068. Table 1 below illustrates otherexample attributes (locations, arrangement, and type) that may be storedas well with the traffic signal ID in a traffic signal data entity.

TABLE 1 3-lens Left turn Traffic Signal ID Latitude Longitude Signal?signal? 2064 42.1052314 −74.3509855 Yes Yes 2065 42.1051817 −74.3508562Yes Yes 2066 42.1051817 −74.3508159 Yes No 2067 42.1051817 −74.3507756Yes No 2068 42.1050235 −74.3507220 Yes NoThese five traffic signals may be grouped into two traffic signalclusters. For example, traffic signals 252 and 254 may be grouped intoone cluster (e.g., cluster ID 847) since they both control left turn andthru traffic, and traffic signals 256, 258, and 260 may be grouped intoanother cluster (e.g., cluster ID 848) since they only control thrutraffic. Table 2 below summarizes:

TABLE 2 Traffic Signal Cluster Traffic Signal ID ID 847 2064 847 2065848 2066 848 2067 848 2068Example intersection maneuvers for FIG. 17 are defined below in Table 3.This intersection may correspond to intersection object ID 849302, whichhas a lane-in link ID 6001 with lanes 1, 2, and, 3 (from the perspectiveof traveling North), and lane-out link IDs 7502, 9423, and 8199.

TABLE 3 Lane In Lane Out Traffic Intersection Link Lane Link LaneQuality Signal Object ID ID ID ID ID Indicator Cluster ID 849302 6001 19423 2 None 848 849302 6001 1 8199 5 Cartooned, 848 high 849302 6001 28199 4 Cartooned, 848 high 849302 6001 3 7502 5 None 847 849302 . . .More records for other incoming roads at this intersection . . .

As shown in Table 3 (and illustrated in FIG. 17), an intersectionmaneuver 300 controlled by traffic signal cluster 847 is that of avehicle traveling North on link 6001 in lane 3 and turning left ontolink 7502 into lane 5. Traffic signal cluster 848 controls all otherintersection maneuvers. For example, cluster 848 controls intersectionmaneuver 302 (e.g., a vehicle traveling North on link 6001 in lane 2onto link 8199 lane 4), intersection maneuver 304 (e.g., a vehicletraveling North on link 6001 in lane 1 onto link 8199 lane 5), andintersection maneuver 306 (e.g., a vehicle traveling North on link 6001in lane 1 onto link 9423 lane 2).

B. Second Exemplary Traffic Signal Representation

FIG. 18 illustrates another example of an intersection 350. In thisexample, both three lens traffic signals (e.g., 356, 358, and 360) andfive-lens traffic signals (e.g., 352 and 354) are present. Because it ispossible that vehicle applications that detect traffic signal phase maybe limited in their ability to handle signals with other than threelenses, five-lens signals can be flagged.

In this example, the five-lens signals allow protected left turns, butleft turns are also permitted (though “unprotected”) on regular greensignals. While the arrows on the five-lens signals pertain only to theleft-turning traffic, the five-lens signals can display a round greensignal which pertains to through traffic as well as left-turningtraffic. Similarly, the three-lens signals are considered to pertain tothe left-turning traffic, because left turns are permitted on regulargreen signals. Thus, since every traffic signal location applies toevery maneuver, there will be only one traffic signal cluster(containing all five traffic signal locations) for this configuration.

FIG. 19 illustrates a data representation of the intersection 350 inFIG. 18. Table 4 below defines the location and attributes of thetraffic signals. Here, traffic signal ID 2071 corresponds to trafficsignal 352, traffic signal ID 2072 corresponds to traffic signal 354,traffic signal ID 2073 corresponds to traffic signal 356, traffic signalID 2074 corresponds to traffic signal 358, and traffic signal ID 2075corresponds to traffic signal 360.

TABLE 4 3-lens Left turn Traffic Signal ID Latitude Longitude Signal?signal? 2071 42.6232314 −74.3649855 No Yes 2072 42.6231817 −74.3648562No Yes 2073 42.6231817 −74.3648159 Yes No 2074 42.6231817 −74.3647756Yes No 2075 42.6230235 −74.3647220 Yes NoAs mentioned above, since every traffic signal location applies to everymaneuver, there is only one traffic signal cluster for thisconfiguration as shown below in Table 5.

TABLE 5 Traffic Signal Cluster ID Traffic Signal ID 849 2071 849 2072849 2073 849 2074 849 2075An exemplary intersection maneuver table for this configuration (forintersection 350 that has intersection object ID 678293), including therelationship to the traffic signal cluster, is shown below in Table 6.

TABLE 6 Lane In Lane Out Traffic Intersection Link Lane Link LaneQuality Signal Object ID ID ID ID ID Indicator Cluster ID 678293 7035 19465 2 None 849 678293 7035 1 8253 5 Cartooned, 849 high 678293 7035 28253 4 Cartooned, 849 high 678293 7035 3 8253 3 Cartooned, 849 high678293 7035 3 7665 5 None 849 678293 . . . More records for otherincoming roads at this intersection . . .As shown in Table 6, intersection maneuver 362 is controlled by trafficsignal cluster 849 where a vehicle traveling North on link 7035 in lane1 turns right onto link 9465 into lane 2. Intersection maneuver 364 iscontrolled by the same cluster and indicates a vehicle traveling Northon link 7035 in lane 1 onto link 8253 lane 5. Intersection maneuver 366indicates a vehicle traveling North on link 7035 in lane 2 onto link8253 lane 4. Intersection maneuver 368 indicates a vehicle travelingNorth on link 7035 in lane 3 onto link 8253 lane 3. Lastly, intersectionmaneuver 370 indicates a vehicle traveling North on link 7035 in lane 3and turning left onto link 7665 into lane 5.

C. Third Exemplary Traffic Signal Representation

In some instances, a traffic signal may dictate that left turns arepermitted “on arrow only.” Consider the intersection illustrated in FIG.18, but with left turns permitted on arrow only. FIG. 20 illustrates adata representation of such an example. In this example, there will betwo clusters: one cluster with just the five-lens signals 352 and 354(associated with the left-turn maneuver), and one cluster with all thesignals (associated with the through and right-turn maneuvers). Thus,the two five-lens signals would belong to two distinct clusters.

Traffic signal locations and attributes for these signals may be asfollows in Table 7 below.

TABLE 7 3-lens Left turn Traffic Signal ID Latitude Longitude Signal?signal? 2083 42.6482314 −74.3299855 No Yes 2084 42.6481817 −74.3298562No Yes 2085 42.6481817 −74.3298159 Yes No 2086 42.6481817 −74.3297756Yes No 2087 42.6480235 −74.3297220 Yes NoTraffic signal clusters for FIG. 20 are as follows: all five trafficsignals will be grouped into one cluster (for through and right-turntraffic), and only the signals with left-turn arrows will be groupedinto another cluster for left-turn traffic as shown below in Table 8.

TABLE 8 Traffic Signal Cluster ID Traffic Signal ID 850 2083 850 2084850 2085 850 2086 850 2087 851 2083 851 2084Exemplary intersection maneuvers for FIG. 20, including the relationshipto the traffic signal clusters, are as follows in Table 9 below.

TABLE 9 Lane In Lane Out Traffic Intersection Link Lane Link LaneQuality Signal Object ID ID ID ID ID Indicator Cluster ID 829920 67822 147728 2 None 850 829920 67822 1 47299 5 Cartooned, 850 high 829920 678222 47299 4 Cartooned, 850 high 829920 67822 3 47299 3 Cartooned, 850 high829920 67822 3 57483 5 None 851 829920 . . . More records for otherincoming roads at this intersection . . .As shown in Table 9, an intersection maneuver 380 controlled by trafficsignal cluster 851 is that of a vehicle traveling North on link 67822 inlane 3 and turning left onto link 57483 into lane 5. Cluster 850controls intersection maneuver 382 (e.g., a vehicle traveling North onlink 67822 in lane 3 onto link 47299 lane 3), intersection maneuver 384(e.g., a vehicle traveling North on link 67822 in lane 2 onto link 47299lane 4), intersection maneuver 386 (e.g., a vehicle traveling North onlink 67822 in lane 1 onto link 47299 lane 5), and intersection maneuver388 (e.g., a vehicle traveling North on link 67822 in lane 1 and turningright onto link 47728 lane 2).

VII. Operation

As mentioned above, a vehicle that has a driver assistance system uses aroad database that has road physical configuration data to provideconvenience features. On a continuous basis, a position of the vehiclerelative to the road network is determined. This function is performedby a positioning system in the vehicle. Using the data in intersectionobjects, lane data entities, and traffic signal data entities, thedriver assistance applications can predict the path ahead of a vehicleas the vehicle travels through intersections. This allows the driverassistance systems to provide convenience features as the vehiclecrosses an intersection. For example, a driver assistance system couldautomatically determinate the appropriate traffic signal and its phaseusing visual object recognition techniques, which require an approximatelocation, arrangement, orientation, height, and type of the trafficsignals, and subsequently provide a warning to a driver (afterreferencing appropriate intersection maneuvers) in the event that thedriver is approaching a red light too fast.

It is intended that the foregoing detailed description be regarded asillustrative rather than limiting, and that it is understood that thefollowing claims including all equivalents are intended to define thescope of the invention.

We claim:
 1. A database the represents roads comprising: a plurality oftraffic signal cluster data structures, wherein each traffic signalcluster data structure includes data representing one or more trafficsignals that operate with identical phases at an intersection to controlone or more intersection maneuvers for traffic entering the intersectionfrom a particular road; and data indicating the one or more intersectionmaneuvers.